The Agronomy Department at Kansas State University seeks a post-doctoral Fellow position to support research efforts related to the Farming Systems team. The applicant for this position will be part of a large, multi-university, collaborative consortium focused on developing digital tools with the regional focused in South Asia and Sub-Saharan Africa. The applicant will be a critical part of a consortium funded by USAID-SIIL lab, Digital Tools, Geospatial and Farming Systems Consortium. A successful applicant should have familiarity with geospatial data and an ability to develop and use geospatial resources drawn from a variety of sources including remote sensing, global map products, and point biophysical data. This includes knowledge of crop simulation models, remote sensing, GIS, spatial statistics, data analytics, expertise in coding (data science), or related areas. Duties: The individual will receive, collect and analyze different types of data, such as satellite imagery, crop physiology, soil and weather data, among others. The person on this position is expected to perform statistical, spatial analysis and crop modeling, summarize data and write reports, both for academia and extension. In addition, the person will also assist and coordinate the work of graduate students from different teams within the Consortium and the partner Countries. Active participation and delivery of training sessions, and presentations for academia and extension. The incumbent will assist in the publication of research and extension results in appropriate media (newsletter, popular press, and refereed journals). For a complete position description and/or to apply, visit: https://careers.k-state.edu/cw/en-us/job/510077/fellow-post-doc.
Minimum Qualifications: • Ph.D. degree in agronomy, geography, environmental science, biosystems engineering, statistics, computer information systesm, or similar discipline by start date. • Excelent computer, data and statistical skills. Strong competency with R, Python, GitHub, ArcGIC/QGIS, GEE, Cloud computing and Systems modeling (APSIM, DSSAT).
Preferred Qualifications: • Knowledge on field crops, field research. • Demonstrated experience working with remote sensing images from multiple sensors. • Demonstrated experience working on crop modeling (APSIM, DSSAT, etc.). • Demonstrated written and oral communications skills, peer-reviewed journals, extension articles, presentations, etc. • Demonstrated interest and ability to perform on field and online trainings for people with different levels of education and different backgrounds. • Demonstrated ability to interact/ coordinate multidisciplinary and large teams, with different levels of education and background.
Additional Salary Information: Salary commensurate with experience.
Internal Number: W0050354
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